Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar
Mangroves are one of the world’s most threatened ecosystems, and Myanmar is regarded as the current mangrove deforestation hotspot globally. Here, we use multi-sensor satellite data and Intensity Analysis to quantify and explain patterns of net and gross mangrove cover change (loss, gain, persistenc...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2020-01-01
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| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ab666d |
| _version_ | 1797747580956835840 |
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| author | Jose Don T De Alban Johanness Jamaludin Donovan Wong de Wen Maung Maung Than Edward L Webb |
| author_facet | Jose Don T De Alban Johanness Jamaludin Donovan Wong de Wen Maung Maung Than Edward L Webb |
| author_sort | Jose Don T De Alban |
| collection | DOAJ |
| description | Mangroves are one of the world’s most threatened ecosystems, and Myanmar is regarded as the current mangrove deforestation hotspot globally. Here, we use multi-sensor satellite data and Intensity Analysis to quantify and explain patterns of net and gross mangrove cover change (loss, gain, persistence) for the 1996–2016 period across all of Myanmar. Net national mangrove cover declined by 52% over 20 years, with annual net loss rates of 3.60%–3.87%. Gross mangrove deforestation was more profound: 63% of the 1996 mangrove extent had been temporarily or permanently converted by 2016. Rice, oil palm, and rubber expansion accounted for most conversion; however, our analysis revealed targeted systematic transitions of mangroves to water (presumably aquaculture) and built-up areas indicated emerging threats for mangroves from those land uses. Restoration programmes facilitated mangrove gains and represent a critical area for investment alongside protection. This study demonstrates the importance of multi-sensor satellite data for national-level mangrove change assessments, along with gross land cover transition analyses to assess landscape dynamics as well as prioritise threats and interventions in an effort to develop holistic strategies that aim to conserve important habitats. |
| first_indexed | 2024-03-12T15:52:39Z |
| format | Article |
| id | doaj.art-402e3bd7b19044299486793af2991318 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:52:39Z |
| publishDate | 2020-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-402e3bd7b19044299486793af29913182023-08-09T15:04:12ZengIOP PublishingEnvironmental Research Letters1748-93262020-01-0115303403410.1088/1748-9326/ab666dImproved estimates of mangrove cover and change reveal catastrophic deforestation in MyanmarJose Don T De Alban0https://orcid.org/0000-0002-1671-5786Johanness Jamaludin1https://orcid.org/0000-0001-7043-4814Donovan Wong de Wen2Maung Maung Than3Edward L Webb4Department of Biological Sciences, National University of Singapore , 117543 SingaporeDepartment of Biological Sciences, National University of Singapore , 117543 SingaporeDepartment of Biological Sciences, National University of Singapore , 117543 SingaporeThe Center for People and Forests (RECOFTC Myanmar), Naypyitaw, 15013 Myanmar, IndiaDepartment of Biological Sciences, National University of Singapore , 117543 SingaporeMangroves are one of the world’s most threatened ecosystems, and Myanmar is regarded as the current mangrove deforestation hotspot globally. Here, we use multi-sensor satellite data and Intensity Analysis to quantify and explain patterns of net and gross mangrove cover change (loss, gain, persistence) for the 1996–2016 period across all of Myanmar. Net national mangrove cover declined by 52% over 20 years, with annual net loss rates of 3.60%–3.87%. Gross mangrove deforestation was more profound: 63% of the 1996 mangrove extent had been temporarily or permanently converted by 2016. Rice, oil palm, and rubber expansion accounted for most conversion; however, our analysis revealed targeted systematic transitions of mangroves to water (presumably aquaculture) and built-up areas indicated emerging threats for mangroves from those land uses. Restoration programmes facilitated mangrove gains and represent a critical area for investment alongside protection. This study demonstrates the importance of multi-sensor satellite data for national-level mangrove change assessments, along with gross land cover transition analyses to assess landscape dynamics as well as prioritise threats and interventions in an effort to develop holistic strategies that aim to conserve important habitats.https://doi.org/10.1088/1748-9326/ab666dagricultural expansionmangrove deforestationmangrove restorationland cover changeGoogle Earth Engineintensity analysis |
| spellingShingle | Jose Don T De Alban Johanness Jamaludin Donovan Wong de Wen Maung Maung Than Edward L Webb Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar Environmental Research Letters agricultural expansion mangrove deforestation mangrove restoration land cover change Google Earth Engine intensity analysis |
| title | Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar |
| title_full | Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar |
| title_fullStr | Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar |
| title_full_unstemmed | Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar |
| title_short | Improved estimates of mangrove cover and change reveal catastrophic deforestation in Myanmar |
| title_sort | improved estimates of mangrove cover and change reveal catastrophic deforestation in myanmar |
| topic | agricultural expansion mangrove deforestation mangrove restoration land cover change Google Earth Engine intensity analysis |
| url | https://doi.org/10.1088/1748-9326/ab666d |
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